Evidence map›Paper›PMID 28489742›Full record

Observational studyMedicine2017

Circulating TNF receptors predict cardiovascular disease in patients with chronic kidney disease.

Eunjin Bae, Ran-Hui Cha, Yong C Kim, Jung N An, Dong K Kim, Kyung D Yoo, Su M Lee, Myoung-Hee Kim, Jung T Park, Shin-Wook Kang and 5 more

Open access · goldAbstract readMulticenter StudyObservational Study
In one paragraph

Observational study in Medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
3.4field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed, 45 citations in OpenAlex.

  1. Trial
  2. Trial
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Review
  9. Review
  10. Article
  11. Plasma Soluble Tumor Necrosis Factor Receptor Concentrations and Clinical Events After Hospitalization: Findings From the ASSESS-AKI and ARID Studies.American journal of kidney diseases : the official journal of the National Kidney Foundation · 2023
    Article
  12. Article
  13. Review
  14. Review
  15. Genes · 2022
    Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Biomarkers of Acute and Chronic Kidney Disease.Annual review of physiology · 2019
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors at 9 institutions in 3 countries.

Eunjin BaeDepartment of Internal Medicine, Gyeongsang National University Changwon Hospital, Changwon Department of Internal Medicine, National Medical Center Department of Internal Medicine, Seoul National University College of Medicine Department of Internal Medicine, Seoul National University Boramae Medical Center, Seoul Department of Internal Medicine, Dongguk University Medical Center, Gyeongju Department of Internal Medicine, Dong-A University, Busan Department of Dental Hygiene, College of Health Science, Eulji University, Seongnam Department of Internal Medicine, Yonsei University College of Medicine, Seoul Department of Internal Medicine, Dongguk University Medical Center, Goyang Kidney Research Institute, Seoul National University, Seoul, Republic of Korea.
Ran-Hui Cha
Yong C Kim
Jung N An
Dong K Kim
Kyung D Yoo
Su M Lee
Myoung-Hee Kim
Jung T Park
Shin-Wook Kang
Jae Y Park
Chun S Lim
Yon S Kim
Seung H Yang
Jung P Lee
Seoul National University · KRYonsei University · KRNew Generation University College · ETSNUH SMG-SNU Boramae Medical Center · KRDong-A University · KRDongguk University · KREulji University · KRGyeongsang National University · KRNational Medical Center · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cardiovascular disease (CVD) is the main public health problem in patients with chronic kidney disease (CKD); however, there is no established biomarker for predicting CVD morbidity and mortality in CKD. The aim of this study was to evaluate the role of circulating tumor necrosis factor receptors (cTNFRs) in predicting CVD risk in CKD patients.We prospectively recruited 984 patients with CKD from 11 centers between 2006 and 2012. The levels of cTNFR1 and cTNFR2 were determined by performing an enzyme-linked immunosorbent assay. During the mean follow-up period of 4 years, 36 patients experienced a CVD event. The median serum concentrations of cTNFR1 and cTNFR2 were 2703.4 (225.6-13,057.7) and 5661.0 (634.9-30,599.6) pg/mL, respectively, and the cTNFR1 level was closely correlated with the cTNFR2 level (r = 0.86, P < .0001). The urinary protein-to-creatinine ratio (UPCR) and estimated glomerular filtration rate (eGFR) were significantly correlated with the cTNFR2 level (r = 0.21 for UPCR, r = -0.67 for eGFR; P < .001 for all). Similar correlations were observed for serum cTNFR1 (r = 0.21 for UPCR, r = -0.75 for eGFR; P < .001 for all). In the Cox proportional hazard analyses, cTNFR1 (hazard ratio [HR] 2.506, 95% confidence interval [CI] 1.186-5.295, P = .016) and cTNFR2 (HR 4.156, 95% CI 1.913-9.030, P < .001) predicted CVD risk even after adjustment for clinical covariates, such as UPCR, eGFR, and high-sensitivity C-reactive protein. cTNFR1 and 2 are associated with CVD and other risk factors in CKD, independently of eGFR and UPCR. Furthermore, cTNFRs could be relevant predictors of CVD in CKD patients.

Indexed as

AdultAgedBlood Chemical AnalysisCardiovascular DiseasesCreatinineEccrine PorocarcinomaEnzyme-Linked Immunosorbent AssayFemaleFollow-Up StudiesGlomerular Filtration RateHumansMaleMiddle AgedProportional Hazards ModelsProspective StudiesReceptors, Tumor Necrosis Factor, Type ICreatinineReceptors, Tumor Necrosis Factor, Type IReceptors, Tumor Necrosis Factor, Type II

Identifiers

PMID28489742
PMCPMC5428576
OpenAlexW2613749900

What OpenQuestion holds

Textmetadata
LicenceCC BY-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.